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The grain flipping probability (GFP) model is used to reproduce the output of micromagnetic ( $\mu $ -mag) simulations several orders of magnitude faster. In this paper, we compare signals from the $\mu $ -magsimulations and the GFP model with readback from a Seagate hard disk drive (HDD). We validate our models by benchmarking the model output against the HDD readback in terms of magnetic write width, and signal-to-noise ratio and bit error rate as a function of the overshoot triplet parameters.

Perpendicular magnetic recording (PMR) in the hard disk drive is approaching its physical limits. In an earlier work, the dedicated servo (DS) recording system has been proposed to provide continuous position error signal for servo, enable higher servo sampling rate, and improve the overall servo performance. A further benefit is that the DS layer results in surface area savings at the data layer. However, it was also reported that the embedded servo layer introduces baseline variation and non-linear transition shift (NLTS) to the readback signal of the data layer. In this paper, we propose novel signal processing techniques to improve the bit error rate (BER) in DS recording. The synchronous averaging technique is proposed to improve the BER in the presence of baseline variation distortions. Further, the servo and data-dependent noise prediction method is proposed to mitigate the effect of the NLTS. Through the use of these techniques the linear density loss from the conventional PMR media is reduced.

Bit-patterned media recording (BPMR) is a promising approach to push back the onset of the superparamagnetic limit faced by conventional granular media recording (CGMR). Previous work in this area has characterized the position jitter and size jitter from fabricated media at recording densities ranging from 0.6 Tera dots per square inch (Tdpsi) to 2.9 Tdpsi, and the characterizations were used to predict expected densities from the BPMR system. In this work, we investigate the impact of a few critical parameters towards the final performance of the BPMR system in terms of the written-in-error (WIE) rate.

Bit-patterned media (BPM) is a promising approach to push back the onset of the superparamagnetic limit faced by conventional continuous granular media. Today, BPM islands can be fabricated at densities higher than can be characterized by existing methods and full bit-patterned media recording (BPMR) is still a long way off. In this work, we rely on simulations to predict how such islands would perform in a real recording scenario. The grain flipping probability (GFP) model is trained via micromagnetic simulations and reproduces the magnetic profiles used to generate readback signals for channel simulations. The geometrical parameters to the micromagnetic simulations, such as the island size variations and island position jitter are characterized from measurements of islands fabricated via e-beam at various channel densities.